def wrapped(*args):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# job_id is always assumed to be the first argument
job_id = args[0]
job = models.OqJob.objects.get(id=job_id)
if job.is_running is False:
# the job was killed, it is useless to run the task
raise JobNotRunning(job_id)
# it is important to save the task id soon, so that
# the revoke functionality can work
EnginePerformanceMonitor.store_task_id(job_id, tsk)
with EnginePerformanceMonitor(
'total ' + task_func.__name__, job_id, tsk, flush=True):
# tasks write on the celery log file
logs.set_level(job.log_level)
check_mem_usage() # log a warning if too much memory is used
try:
# run the task
return task_func(*args)
finally:
# save on the db
CacheInserter.flushall()
# the task finished, we can remove from the performance
# table the associated row 'storing task id'
models.Performance.objects.filter(
oq_job=job,
operation='storing task id',
task_id=tsk.request.id).delete()
def wrapped(*args, **kwargs):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# job_id is always assumed to be the first argument passed to
# the task, or a keyword argument
# this is the only required argument
job_id = kwargs.get('job_id') or args[0]
with EnginePerformanceMonitor(
'totals per task', job_id, tsk, flush=True):
job = models.OqJob.objects.get(id=job_id)
# it is important to save the task ids soon, so that
# the revoke functionality implemented in supervisor.py can work
EnginePerformanceMonitor.store_task_id(job_id, tsk)
with EnginePerformanceMonitor(
'loading calculation object', job_id, tsk, flush=True):
calculation = job.calculation
# Set up logging via amqp.
if isinstance(calculation, models.HazardCalculation):
logs.init_logs_amqp_send(level=job.log_level,
calc_domain='hazard',
calc_id=calculation.id)
else:
logs.init_logs_amqp_send(level=job.log_level,
calc_domain='risk',
calc_id=calculation.id)
try:
# Tasks can be used in the `execute` or `post-process` phase
if job.is_running is False:
raise JobCompletedError('Job %d was killed' % job_id)
elif job.status not in ('executing', 'post_processing'):
raise JobCompletedError(
'The status of job %d is %s, should be executing or '
'post_processing' % (job_id, job.status))
# else continue with task execution
res = task_func(*args, **kwargs)
# TODO: should we do something different with JobCompletedError?
except Exception, err:
logs.LOG.critical('Error occurred in task: %s', err)
logs.LOG.exception(err)
raise
else:
def wrapped(*args, **kwargs):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# job_id is always assumed to be the first argument passed to
# the task, or a keyword argument
# this is the only required argument
job_id = kwargs.get('job_id') or args[0]
job = models.OqJob.objects.get(id=job_id)
if job.is_running is False:
# the job was killed, it is useless to run the task
return
# it is important to save the task ids soon, so that
# the revoke functionality implemented in supervisor.py can work
EnginePerformanceMonitor.store_task_id(job_id, tsk)
with EnginePerformanceMonitor('total ' + task_func.__name__,
job_id,
tsk,
flush=True):
with EnginePerformanceMonitor('loading calculation object',
job_id,
tsk,
flush=True):
calculation = job.calculation
# Set up logging via amqp.
if isinstance(calculation, models.HazardCalculation):
logs.init_logs_amqp_send(level=job.log_level,
calc_domain='hazard',
calc_id=calculation.id)
else:
logs.init_logs_amqp_send(level=job.log_level,
calc_domain='risk',
calc_id=calculation.id)
try:
res = task_func(*args, **kwargs)
except Exception, err:
logs.LOG.critical('Error occurred in task: %s', err)
logs.LOG.exception(err)
raise
else:
def wrapped(*args):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# job_id is always assumed to be the first argument
job_id = args[0]
job = models.OqJob.objects.get(id=job_id)
if job.is_running is False:
# the job was killed, it is useless to run the task
return
# it is important to save the task id soon, so that
# the revoke functionality can work
EnginePerformanceMonitor.store_task_id(job_id, tsk)
with EnginePerformanceMonitor(
'total ' + task_func.__name__, job_id, tsk, flush=True):
with EnginePerformanceMonitor(
'loading calculation object', job_id, tsk, flush=True):
calculation = job.calculation
# tasks write on the celery log file
logs.init_logs(
level=job.log_level,
calc_domain='hazard' if isinstance(
calculation, models.HazardCalculation) else'risk',
calc_id=calculation.id)
try:
return task_func(*args), None
except:
etype, exc, tb = sys.exc_info()
tb_str = ''.join(traceback.format_tb(tb))
return '%s\n%s' % (exc, tb_str), etype
finally:
CacheInserter.flushall()
# the task finished, we can remove from the performance
# table the associated row 'storing task id'
models.Performance.objects.filter(
oq_job=job,
operation='storing task id',
task_id=tsk.request.id).delete()
def wrapped(*args, **kwargs):
"""
Initialize logs, make sure the job is still running, and run the task
code surrounded by a try-except. If any error occurs, log it as a
critical failure.
"""
# job_id is always assumed to be the first argument passed to
# the task, or a keyword argument
# this is the only required argument
job_id = kwargs.get('job_id') or args[0]
job = models.OqJob.objects.get(id=job_id)
if job.is_running is False:
# the job was killed, it is useless to run the task
return
# it is important to save the task ids soon, so that
# the revoke functionality implemented in supervisor.py can work
EnginePerformanceMonitor.store_task_id(job_id, tsk)
with EnginePerformanceMonitor(
'total ' + task_func.__name__, job_id, tsk, flush=True):
with EnginePerformanceMonitor(
'loading calculation object', job_id, tsk, flush=True):
calculation = job.calculation
# Set up logging via amqp.
if isinstance(calculation, models.HazardCalculation):
logs.init_logs_amqp_send(level=job.log_level,
calc_domain='hazard',
calc_id=calculation.id)
else:
logs.init_logs_amqp_send(level=job.log_level,
calc_domain='risk',
calc_id=calculation.id)
try:
res = task_func(*args, **kwargs)
except Exception, err:
logs.LOG.critical('Error occurred in task: %s', err)
logs.LOG.exception(err)
raise
else:
